I. Field of the Invention
The present invention relates to the field of business intelligence and in particular, to apparatus, systems, and methods for facilitating dynamic on-demand context sensitive cluster analysis in business intelligence systems.
II. Description of Related Art
In modern organizations, strategic planning can be central to the evaluation of business risks and for efficient and optimal deployment of organizational resources including human resources. For example, strategic planning may involve determining current resource demands and utilization—including both human and material resources, forecasting future resource demands, and planning to satisfy current and estimated future resource demands in a cost optimal manner. Accordingly, many organizations use a variety of systems such as Enterprise Resource Planning (“ERP”) systems, which facilitate automated organizational integration of management information. Typically, ERP systems take the form of a complex software suite facilitating the flow of information between various organizational entities such as sales, finance, accounting, manufacturing, human resources, etc.
Business Intelligence (“BI”) systems can process data generated by ERP systems to calculate key performance indicators for various organizational entities and processes and drive decisions. For example, information in ERP systems may be aggregated by a BI system in a variety of ways to match the specific needs of departments. For example, the data aggregation may occur in one fashion for the sales department and in another manner for manufacturing. BI systems thus support planning, budgeting, forecasting and reporting, including, for example, the setting of targets for organizational entities and processes and the monitoring of progress toward those targets.
Traditional BI systems exhibit several drawbacks because of their inherent complexity. For example, the complexity of BI systems makes deployment and customization for specific applications difficult. In addition, BI systems are not easily adapted to deal with unstructured or semi-structured data or to changes in the format of the underlying data. Further, non-technical organizational staff may often experience difficulty in using BI systems. The lack of employee comfort or competence with BI systems can lead to problems in quickly generating intelligence for a specific department or application. Moreover, the large cost and support overheads associated with ERP and BI systems are an impediment to their wide use and deployment. Finally, while traditional ERP and BI systems may permit calculations of various metrics, these systems do not facilitate analysis of the impact of one or more populations on the calculated metrics. Therefore, organizations are often deprived of the competitive advantage of good business intelligence.
Thus, there is a need for apparatus, systems and methods that facilitate dynamic on-demand context sensitive cluster analysis in business intelligence systems in a cost and resource optimal manner.